This paper presents a new model for adaptive filter with the least-mean-square (LMS) scheme to train the mask operation on low resolution images. The adaptive filter theory with adaptive least-mean-square scheme (ALMSS) uses the training mask for moving object detection and tracking. However, the successful moving objects detection in a real surrounding environment is a difficult task due to noise issues such as fake motion or Gaussian noise. Many approaches have been developed in constrained environments to detect and track moving objects. On the other hand, the ALMSS approach can effectively reduce the noise with low computing cost in both fake motion and Gaussian noise environments. The experiments on real scenes indicate that the proposed ALMSS method is effective for moving object detection and tracking in real-time.